Figure 3. Analysis of community networks vs. individual inference methods.

(a) The plot shows the overall score, which summarizes performance across the E. coli, S. cerevisiae, and in silico networks, for individual inference methods or various combinations of integrated methods. The first boxplot depicts the performance distribution of individual inference methods (K=1). Subsequent boxplots show the performance when integrating K>1 randomly sampled methods. The red bar shows the performance when integrating all methods (K=29). Boxplots depict performance distributions with respect to the minimum, the maximum and the three quartiles. (b) The probability that the community network ranks among the top x% of the K individual methods used to construct the community network. The diagonal shows the expected performance when choosing an individual method (K=1). (c) The integration of complementary methods is particularly beneficial. The first boxplot shows the performance of individual methods from clusters 1–3 (as defined in Fig. 2b). The second and third boxplots show performance of community networks obtained by integrating three randomly selected inference methods: (i) from the same cluster, or (ii) from different clusters. (d) The plots show the overall score for an initial community network formed by integrating all individual methods (open circles, blue) except for the best five and worst five. One-by-one the worst five (left panel) and best five (right panel) methods are added to form additional community networks (filled circles, red).